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Impact of Vessel Suppressed-CT on Diagnostic Accuracy in Detection of Pulmonary Metastasis and Reading Time.
- Source :
-
Academic radiology [Acad Radiol] 2021 Jul; Vol. 28 (7), pp. 988-994. Date of Electronic Publication: 2020 Feb 06. - Publication Year :
- 2021
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Abstract
- Rationale and Objectives: To assess if vessel suppression (VS) improves nodule detection rate, interreader agreement, and reduces reading time in oncologic chest computed tomography (CT).<br />Material and Methods: One-hundred consecutive oncologic patients (65 male; median age 60y) who underwent contrast-enhanced chest CT were retrospectively included. For all exams, additional VS series (ClearRead CT, Riverrain Technologies, Miamisburg) were reconstructed. Two groups of three radiologists each with matched experience were defined. Each group evaluated the SD-CT as well as VS-CT. Each reader marked the presence, size, and position of pulmonary nodules and documented reading time. In addition, for the VS-CT the presence of false positive nodules had to be stated. Cohen's Kappa (k) was used to calculate the interreader-agreement between groups. Reading time was compared using paired t test.<br />Results: Nodule detection rate was significantly higher in VS-CT compared to the SD-CT (+21%; p <0.001). Interreader-agreement was higher in the VS-CT (k = 0.431, moderate agreement) compared to SD-CT (k = 0.209, fair agreement). Almost all VS-CT series had false positive findings (97-99 out of 100). Average reading time was significantly shorter in the VS-CT compared to the SD-CT (154 ± 134vs. 194 ± 126; 21%, p<0.001).<br />Conclusions: Vessel suppression increases nodule detection rate, improves interreader agreement, and reduces reading time in chest CT of oncologic patients. Due to false positive results a consensus reading with the SD-CT is essential.<br /> (Copyright © 2020 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.)
Details
- Language :
- English
- ISSN :
- 1878-4046
- Volume :
- 28
- Issue :
- 7
- Database :
- MEDLINE
- Journal :
- Academic radiology
- Publication Type :
- Academic Journal
- Accession number :
- 32037256
- Full Text :
- https://doi.org/10.1016/j.acra.2020.01.014